MeLOn
ScaleVariables.m File Reference

Functions

size(X zeros ()
 
calculate mean stdOfOutput (i)
 
calculate standard deviation Ynew (:, i)
 

Variables

 function [Xnew, Ynew, meanOfOutput, stdOfOutput]
 
Artur M Schweidtmann and Alexei Lapkin
 
scaled inputs Ynew = zeros(size(Y))
 
scaled outputs meanOfOutput = zeros(size(Y,2))
 
 stdOfOutput = zeros(size(Y,2))
 
Scale input variables to[0, 1] for i
 

Function Documentation

◆ stdOfOutput()

calculate mean stdOfOutput ( i  )

◆ Ynew()

calculate standard deviation Ynew ( ,
i   
)

◆ zeros()

size(X zeros ( )
virtual

Variable Documentation

◆ function

Initial value:
= ScaleVariables(X,Y,lb,ub)
% Copyright (c) by Eric Bradford

◆ i

end Scale output variables to zero mean and unit variance for i
Initial value:
= 1 : size(X,2)
Xnew(:,i) = (X(:,i)-lb(i)) / (ub(i)-lb(i))

◆ Lapkin

end return function Artur M Schweidtmann and Alexei Lapkin

◆ meanOfOutput

scaled outputs meanOfOutput = zeros(size(Y,2))

◆ stdOfOutput

stdOfOutput = zeros(size(Y,2))

◆ Ynew

scaled inputs Ynew = zeros(size(Y))
c
end c
Definition: Train_GP_and_return_hyperparameters.m:243
i
Scale input variables to[0, 1] for i
Definition: ScaleVariables.m:11
X
lb+(ub-lb) .*X X
Definition: example_training_of_ANN.m:36
Y
Scale inputs onto interval[lb, ub] Y
Definition: example_training_of_ANN.m:38
size
Xnew size()
ub
Define Lower bound of inputs ub
Definition: example_training_of_ANN.m:26
Xnew
id Xnew()
lb
Input dimension of data GP lb
Definition: example_training_of_ANN.m:25